trait HasAssociationAttributes extends HasModelAttributes
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- abstract def algorithmName: Option[String]
The algorithm name is free-type and can be any description for the specific algorithm that produced the model.
The algorithm name is free-type and can be any description for the specific algorithm that produced the model. This attribute is for information only.
- Definition Classes
- HasModelAttributes
- abstract def avgNumberOfItemsPerTA: Option[Double]
The average number of items contained in a transaction.
- abstract def functionName: MiningFunction
Describe the kind of mining model, e.g., whether it is intended to be used for clustering or for classification.
Describe the kind of mining model, e.g., whether it is intended to be used for clustering or for classification.
- Definition Classes
- HasModelAttributes
- abstract def isScorable: Boolean
Indicates if the model is valid for scoring.
Indicates if the model is valid for scoring. If this attribute is true or if it is missing, then the model should be processed normally. However, if the attribute is false, then the model producer has indicated that this model is intended for information purposes only and should not be used to generate results.
- Definition Classes
- HasModelAttributes
- abstract def lengthLimit: Option[Int]
The maximum number of items contained in a rule which was used to limit the number of rules.
- abstract def maxNumberOfItemsPerTA: Option[Int]
The number of items contained in the largest transaction.
- abstract def minimumConfidence: Double
The minimum confidence value satisfied by all rules.
The minimum confidence value satisfied by all rules. Confidence is calculated as (support (rule) / support(antecedent)).
- abstract def minimumSupport: Double
The minimum relative support value (#supporting transactions / #total transactions) satisfied by all rules.
- abstract def modelName: Option[String]
Identifies the model with a unique name in the context of the PMML file.
Identifies the model with a unique name in the context of the PMML file. This attribute is not required. Consumers of PMML models are free to manage the names of the models at their discretion.
- Definition Classes
- HasModelAttributes
- abstract def numberOfItems: Int
The number of different items contained in the input data.
The number of different items contained in the input data. This number may be greater than or equal to the number of items contained in the model. The value will be greater if any items in the input data are excluded from the model, as a consequence of not being referenced by the model.
- abstract def numberOfItemsets: Int
The number of itemsets contained in the model.
- abstract def numberOfRules: Int
The number of rules contained in the model.
- abstract def numberOfTransactions: Int
The number of transactions contained in the input data.
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- def isAssociationRules: Boolean
Tests if this is a association rules model.
Tests if this is a association rules model.
- Definition Classes
- HasModelAttributes
- def isClassification: Boolean
Tests if this is a classification model.
Tests if this is a classification model.
- Definition Classes
- HasModelAttributes
- def isClustering: Boolean
Tests if this is a clustering model.
Tests if this is a clustering model.
- Definition Classes
- HasModelAttributes
- final def isInstanceOf[T0]: Boolean
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- def isMixed: Boolean
Tests if this is a mixed model.
Tests if this is a mixed model.
- Definition Classes
- HasModelAttributes
- def isRegression: Boolean
Tests if this is a regression model.
Tests if this is a regression model.
- Definition Classes
- HasModelAttributes
- def isSequences: Boolean
Tests if this is a sequences model.
Tests if this is a sequences model.
- Definition Classes
- HasModelAttributes
- def isTimeSeries: Boolean
Tests if this is a time series model.
Tests if this is a time series model.
- Definition Classes
- HasModelAttributes
- final def ne(arg0: AnyRef): Boolean
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